A Philosopher's Blog

Weight Loss, Philosophy & Science

Posted in Philosophy, Reasoning/Logic, Running, Science, Sports/Athletics by Michael LaBossiere on August 2, 2017

When I was young and running 90-100 miles a week, I could eat all the things without gaining weight. Time is doubly cruel in that it slowed my metabolism and reduced my ability to endure high mileage. Inundated with the usual abundance of high calorie foods, I found I was building an unsightly pudge band around my middle. My first reaction was to try to get back to my old mileage, but I found that I now top out at 70 miles a week and anything more starts breaking me down. Since I could not exercise more, I was faced with the terrible option of eating less. Being something of an expert on critical thinking, I dismissed all the fad diets and turned to science to glean the best way to beat the bulge. Being a philosopher, I naturally misapplied the philosophy of science to this problem with some interesting results.

Before getting into the discussion, I am morally obligated to point out that I am not a medical professional. As such, what follows should be regarded with due criticism and you should consult a properly credentialed expert before embarking on changes to your exercise or nutrition practices. Or you might die. Probably not; but maybe.

As any philosopher will tell you, while the math used in science is deductive (the premises are supposed to guarantee the conclusion with certainty) scientific reasoning is inductive (the premises provide some degree of support for the conclusion that is less than complete). Because of this, science suffers from the problem of induction. In practical terms, this means that no matter how carefully the reasoning is conducted and no matter how good the evidence is, the conclusion drawn from the evidence can still be false. The basis for this problem is the fact that inductive reasoning involves a “leap” from the evidence/premises (what has been observed) to the conclusion (what has not been observed). Put bluntly, inductive reasoning can always lead to a false conclusion.

Scientists and philosophers have long endeavored to make science a deductive matter. For example, Descartes believed that he could find truths that he could know with certainty and then use valid deductive reasoning to generate a true conclusion with absolute certainty. Unfortunately, this science of certainty is the science of the future and always will be. So, we are stuck with induction.

The problem of induction obviously applies to the sciences that study nutrition, exercise and weight loss and, as such, the conclusions made in these sciences can always be wrong. This helps explain why the recommendations about these matters change relentlessly.

While there are philosophers of science who would disagree, science is mostly a matter of trying to figure things out by doing the best that can be done at the time. This is limited by the resources (such as technology) available at the time and by human epistemic capabilities. As such, whatever science is presenting at the moment is almost certainly at least partially wrong; but the wrongs get reduced over time. Or increase sometimes. This is true of all the sciences—consider, for example, the changes in physics since Thales began it. This also helps explain why the recommendations about diet and exercise change constantly.

While science is sometimes presented as a field of pure reason outside of social influences, science is obviously a social activity conducted by humans. Because of this, science is influence by the usual social factors and human flaws. For example, scientists need money to fund their research and can thus be vulnerable to corporations looking to “prove” various claims that are in their interest. As another example, scientific matters can become issues of political controversy, such as evolution and climate change. This politicization tends to derange science. As a final example, scientists can be motivated by pride and ambition to fudge or fake results. Because of these factors, the sciences dealing with nutrition and exercise are significantly corrupted and this makes it difficult to make a rational judgment about which claims are true. One excellent example is how the sugar industry paid scientists at Harvard to downplay the health risks presented by sugar and play up those presented by fat. Another illustration is the fact that the food pyramid endorsed by the US government has been shaped by the food industries rather than being based entirely on good science.

Given these problems it might be tempting to abandon mainstream science and go with whatever fad or food ideology one finds appealing. That would be a bad idea. While science suffers from these problems, mainstream science is vastly better than the nonscientific alternatives—they tend to have all of the problems of science without having its strengths. So, what should one do? The rational approach is to accept the majority opinion of the qualified and credible experts. One should also keep in mind the above problems and approach the science with due skepticism.

So, what are some of the things the best science of today say about weight loss? First, humans evolved as hunter-gatherers and getting enough calories was a challenge. As such, humans tend to be very good at storing energy in the form of fat which is one reason the calorie rich environment of modern society contributes to obesity. Crudely put, it is in our nature to overeat—because that once meant the difference between life and death.

Second, while exercise does burn calories, it burns far less than many imagine. For most people, the majority of calorie burning is a result of the body staying alive. As an example, I burn about 4,000 calories on my major workout days (estimated based on my Fitbit and activity calculations). But, about 2,500 of those calories are burned just staying alive. On those days I work out about four hours and I am fairly active the rest of the day. As such, while exercising more will help a person lose weight, the calorie impact of exercise is surprisingly low—unless you are willing to commit considerable time to exercise. That said, you should exercise—in addition to burning calories it has a wide range of health benefits.

Third, hunger is a function of the brain and the brain responds differently to different foods. Foods high in protein and fiber create a feeling of fullness that tends to turn off the hunger signal. Foods with a high glycemic index (like cake) tend to stimulate the brain to cause people to consume more calories. As such, manipulating your brain is an effective way to increase the chance of losing weight. Interestingly, as Aristotle argued, habituation to foods can train the brain to prefer foods that are healthier—that is, you can train yourself to prefer things like nuts, broccoli and oatmeal over cookies, cake, and soda. This takes time and effort, but can obviously be done.

Fourth, weight loss has diminishing returns: as one loses weight, one’s metabolism slows and less energy is needed. As such, losing weight makes it harder to lose weight, which is something to keep in mind.  Naturally, all of these claims could be disproven in the next round of scientific investigation—but they seem quite reasonable now.


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Picking between Studies

Posted in Philosophy, Reasoning/Logic by Michael LaBossiere on January 31, 2014
Illustration of swan-necked flask experiment u...

(Photo credit: Wikipedia)

In my last essay I looked briefly at how to pick between experts. While people often reply on experts when making arguments, they also rely on studies (and experiments). Since most people do not do their own research, the studies mentioned are typically those conducted by others. While using study results in an argument is quite reasonable, making a good argument based on study results requires being able to pick between studies rationally.

Not surprisingly, people tend to pick based on fallacious reasoning. One common approach is to pick a study based on the fact that it agrees with what you already believe. This is rather obviously not good reasoning: to infer that something is true simply because I believe it gets things backwards. It should be first established that a claim is probably true, then it is reasonable to believe it.

Another common approach is to accept a study as correct because the results match what you really want to be true. For example, a liberal might accept a study that claims liberals are smarter and more generous than conservatives.  This sort of “reasoning” is the classic fallacy of wishful thinking. Obviously enough, wishing that something is true (or false) does not prove that the claim is true (or false).

In some cases, people try to create their own “studies” by appealing to their own anecdotal data about some matter. For example, a person might claim that poor people are lazy based on his experience with some poor people. While anecdotes can be interesting, to take an anecdote as evidence is to fall victim to the classic fallacy of anecdotal evidence.

While fully assessing a study requires expertise in the relevant field, non-experts can still make rational evaluations of studies, provided that they have the relevant information about the study. The following provides a concise guide to studies—and experiments.

In normal use, people often jam together studies and experiments. While this is fine for informal purposes, this distinction is actually important. A properly done controlled cause-to-effect experiment is the gold standard of research, although it is not always a viable option.

The objective of the experiment is to determine the effect of a cause and this is done by the following general method. First, a random sample is selected from the population. Second, the sample is split into two groups: the experimental group and the control group. The two groups need to be as alike as possible—the more alike the two groups, the better the experiment.

The experimental group is then exposed to the causal agent while the control group is not. Ideally, that should be the only difference between the groups. The experiment then runs its course and the results are examined to determine if there is a statistically significant difference between the two. If there is such a difference, then it is reasonable to infer that the causal factor brought about the difference.

Assuming that the experiment was conducted properly, whether or not the results are statistically significant depends on the size of the sample and the difference between the control group and experimental group. The key idea is that experiments with smaller samples are less able to reliably capture effects. As such, when considering whether an experiment actually shows there is a causal connection it is important to know the size of the sample used. After all, the difference between the experimental and control groups might be rather large, but might not be significant. For example, imagine that an experiment is conducted involving 10 people. 5 people get a diet drug (experimental group) while 5 do not (control group). Suppose that those in the experimental group lose 30% more weight than those in the control group. While this might seem impressive, it is actually not statistically significant: the sample is so small, the difference could be due entirely to chance. The following table shows some information about statistical significance.

Sample Size (Control group + Experimental Group)

Approximate Figure That The Difference Must Exceed

To Be Statistically Significant

(in percentage points)

10 40
100 13
500 6
1,000 4
1,500 3

While the experiment is the gold standard, there are cases in which it would be impractical, impossible or unethical to conduct an experiment. For example, exposing people to radiation to test its effect would be immoral. In such cases studies are used rather than experiments.

One type of study is the Nonexperimental Cause-to-Effect Study. Like the experiment, it is intended to determine the effect of a suspected cause. The main difference between the experiment and this sort of study is that those conducting the study do not expose the experimental group to the suspected cause. Rather, those selected for the experimental group were exposed to the suspected cause by their own actions or by circumstances. For example, a study of this sort might include people who were exposed to radiation by an accident. A control group is then matched to the experimental group and, as with the experiment, the more alike the groups are, the better the study.

After the study has run its course, the results are compared to see if these is a statistically significant difference between the two groups. As with the experiment, merely having a large difference between the groups need not be statistically significant.

Since the study relies on using an experimental group that was exposed to the suspected cause by the actions of those in the group or by circumstances, the study is weaker (less reliable) than the experiment. After all, in the study the researchers have to take what they can find rather than conducting a proper experiment.

In some cases, what is known is the effect and what is not known is the cause. For example, we might know that there is a new illness, but not know what is causing it. In these cases, a Nonexperimental Effect-to-Cause Study can be used to sort things out.

Since this is a study rather than an experiment, those in the experimental group were not exposed to the suspected cause by those conducting the study. In fact, the cause it not known, so those in the experimental group are those showing the effect.

Since this is an effect-to-cause study, the effect is known, but the cause must be determined. This is done by running the study and determining if these is a statistically significant suspected causal factor. If such a factor is found, then that can be tentatively taken as a causal factor—one that will probably require additional study. As with the other study and experiment, the statistical significance of the results depends on the size of the study—which is why a study of adequate size is important.

Of the three methods, this is the weakest (least reliable). One reason for this is that those showing the effect might be different in important ways from the rest of the population. For example, a study that links cancer of the mouth to chewing tobacco would face the problem that those who chew tobacco are often ex-smokers. As such, the smoking might be the actual cause. To sort this out would involve a study involving chewers who are not ex-smokers.

It is also worth referring back to my essay on experts—when assessing a study, it is also important to consider the quality of the experts conducting the study. If those conducting the study are biased, lack expertise, and so on, then the study would be less credible. If those conducting it are proper experts, then that increases the credibility of the study.

As a final point, there is also a reasonable concern about psychological effects. If an experiment or study involves people, what people think can influence the results. For example, if an experiment is conducted and one group knows it is getting pain medicine, the people might be influenced to think they are feeling less pain. To counter this, the common approach is a blind study/experiment in which the participants do not know which group they are in, often by the use of placebos. For example, an experiment with pain medicine would include “sugar pills” for those in the control group.

Those conducting the experiment can also be subject to psychological influences—especially if they have a stake in the outcome. As such, there are studies/experiments in which those conducting the research do not know which group is which until the end. In some cases, neither the researchers nor those in the study/experiment know which group is which—this is a double blind experiment/study.

Overall, here are some key questions to ask when picking a study:

Was the study/experiment properly conducted?

Was the sample size large enough?

Were the results statistically significant?

Were those conducting the study/experiment experts?

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Gluten, Celebrity Diets and Critical Thinking

Posted in Medicine/Health, Reasoning/Logic by Michael LaBossiere on December 5, 2011
Oat grains in their husks

Image via Wikipedia

Having been around a while, I have seen celebrity endorsed fad diets come and go. One of the most recent trends is the gluten-free diet. This diet has been presented as a way of losing weight and some have even suggested that it can help with autism. While various celebrities have promoted this diet, health advice from celebrities should be subject to proper critical assessment.

As might be imagined, people have a tendency to confuse celebrity status with expertise. That is, people often believe what a celebrity claims is true because the celebrity is famous. However, while reputation is a factor in assessing expertise, the reputation has to be within the field in which the person is making the claim. So, for example, a person’s fame as an actor has no relevance to her ability to make credible claims about diets. There is also the fact that a person’s expertise depends primarily not on their fame but on such factors as education, experience, and  accomplishments within the field. A lack of excessive bias is also an important factor in assessing the claims of an expert.  Accepting claims based on unwarranted authority (such as buying into a diet simply because a celebrity endorses it) would be to fall victim to a fallacious argument from authority.

Relying on experts is not, of course, a fallacy. However, one has to be careful to turn to the right experts-that is, people who have the knowledge and experience to be be able to make informed claims and who have the objectivity and lack of bias to be trustworthy. As might be imagined, celebrities who are pushing specific products would tend to be lacking in both areas.

As a specific example, consider the fad of gluten free diets. Like some fad diets, there is some truth behind the fad.  In the case of gluten, there is a condition called Celiac Disease. People with this disease need to have a gluten free diet in order to avoid various health problems.  While this is a real condition, only about 1% of the US population has Celiac Disease. As such, 99% of the population does not need a gluten free diet.

However, those pushing a gluten free diet claim that it has health benefits for people who do not have this disease. If so, then the diet would be worth considering. However, there seems to be no objective scientific data supporting these claims-thus there would seem to be no reason for people who lack the disease to go on such a diet.

But, one of the main reasons for going on a diet is weight loss and the gluten free diet has been pushed as a means of losing weight.  However, the evidence is that the gluten free diet has no special capacity to cause weight loss. See, for example,  Wendy Marcason’s “Is the Evidence to Support the Claim that a Gluten-Free Diet Should Be Used for Weight Loss”, page 1786 in in the November 2011 Journal of the American Dietetic Association.

As has long been known, weight loss is primarily a matter of expending more calories that you take in. While gluten products do have calories, gluten calories are simply calories-as are non-gluten calories. In fact, as Marcason points out, some gluten free products have more calories and fat than their gluten containing counterparts. Eating such products in favor of the lower calorie versions will, obviously enough, not promote weight loss.

From the standpoint of thinking well about these matters, there are three main points to take away from this. First, celebrities are not (unless they are also health experts) experts on dieting and health. Second, advice about dieting should be sought from the actual experts-who are generally not celebrities and who tend to give mundane advice like “eat less, eat better and exercise more”. Third, losing weight is a matter of expending more calories than one takes in and there is obviously no fad diet that can change this basic equation. Naturally, a good diet is also more than just a matter of calories-there is also the rather critical matter of nutrients (ironically, there are people who are both obese and malnourished at the same time).  But, do not take my word for it-listen to the experts.

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Fighting Time

Posted in Medicine/Health, Philosophy, Running, Sports/Athletics by Michael LaBossiere on October 1, 2011
Journal of Aging and Health

Image via Wikipedia

Although scientists and philosophers have speculated that time is not real (though they have never missed lunchtime on that basis), it certainly seems to be real enough as an opponent.

When I hit 40 and won my first Master’s award (Master=old), I started looking into the impact of aging on running. I had, of course, learned about aging back when I took anatomy and physiology, but this was a bit more real. While I will spare you the details, the gist of it is that once we humans hit our mid to late twenties, we start a slow spiral downwards (or rapid, depending on how one handles it). While everyone notices this, competitive runners tend to notice it more. This is not because we are somehow more realistic or more perceptive. Rather, it is the fact that we get to see the aging play out it cold, objective numbers as our times get slower and slower. There is also the subjective factor: runs seem to hurt more, one’s stride feels less snappy, and recovery seems to take longer. Or maybe gravity is just increasing in a selective manner-that is, under me.

Fortunately, there is some compensation for these harsh facts: running and exercise in general can be used to fight time. Running is especially effective at literally keeping the cells younger (no magic, just biology) which is why runners often look younger than they are (or, more aptly, other folks look older than they should). Exercise is also critical to resisting two major problems of aging: muscle and bone loss. Like an eroding sandbar, time eats away at the very makeup of our body. Fortunately, exercise that builds muscle and bone can slow down this loss, thus enabling the body to handle aging better. Exercise can also help with balance. Since falls tend to be a major threat to the elderly, building up your fall avoidance and resistance is a smart thing.

Exercise alone, as they say about losing weight, is not enough: diet is also important. When I was young, it mattered less what I ate (or so I thought). Being older, I have less margin of junk (so to speak), and I have had to change my diet to be significantly more healthy. What is actually pretty cool is that what I eat now is not only better for me, but it actually tastes better than much of what I used to eat. It does help that I am not a poor graduate student: eating well is not a luxury, but it is not as cheap as ramen and generic rice puff cereal.

My main goal is not to live really long (although I am fine with that) but to have a good life as long as possible. That seems to be something almost any of us can do, with a little planning and a lot of sweat.

In the end, however, time kills us all. But all races must end and the glory is in the running.

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The Deficit and Weight

Posted in Law, Philosophy, Politics by Michael LaBossiere on July 14, 2011
Map of average per capita state tax revenue, 2007.

Image via Wikipedia

In some ways, the deficit is analogous to being overweight. In the case of the deficit, we have too much debt that results either from too much spending or too little income (or both). In the case of being overweight, one has too much fat that results from consuming too much or exercising too little (or both).

As with being overweight, the deficit has a simple solution. In the case of being overweight, the simple solution is to intake fewer calories and expend more calories. Or, crudely put, eat less and exercise more. It is possible to do just one (eat less or exercise more), but this would be less effective.

In the case of the deficit, the simple solution is to intake more money or expend less (or both). Or, crudely put, tax more and spend less. Of course, it is possible to take just one approach: tax more or spend less. Of course, as with the matter of weight, this would presumably be less effective. It can, however, be argued that it is more desirable to take one approach rather than the other. For example, a stereotypical conservative might argue that spending should be cut without there being any increase in taxes. As another example, a stereotypical liberal might argue that there should be tax increases without any decrease in spending.

My view is that it makes excellent sense to approach the deficit by reducing spending and also increasing revenue. Just as with weight loss, this should be done in a sensible manner. In this case, by cutting excess spending and requiring people (and corporations are people) to bear a fair share of the burden of public services (such as fighting wars for the strategic interests of American businesses).

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